SPIDER improves spatial transcriptomics data using single-cell RNA sequencing
Spatial transcriptomics is a powerful technology that allows researchers to measure gene activity while preserving information about where cells are located within a tissue. Unlike traditional RNA sequencing, which can lose this spatial information when tissue is broken apart, ...
Spatial RNA sequencing reveals how microbes and host cells interact in the gut
The human gut is home to trillions of microbes that constantly interact with each other and with the cells lining the intestine. These interactions influence digestion, immune responses, and even disease development. However, studying these relationships has been difficult ...
Immune cells remember their location
Researchers in Bonn use an AI algorithm to reconstruct the spatial origin of macrophages A new AI-based method reconstructs spatial information about where immune cells were originally located in an organ, even after these cells have been removed from ...
Mapping gene activity in three dimensions with volumetric DNA microscopy
Biological tissues are three dimensional structures. Cells are arranged in complex layers and neighborhoods, and their position often influences how they behave. However, many spatial transcriptomics methods rely on very thin tissue sections. While these techniques provide valuable information, ...
ULMnet – inferring physical cell-cell communication networks from scRNAseq data using univariate linear models
Cells in tissues communicate in many ways, by sending signals over distance or by directly touching neighboring cells. Single-cell RNA sequencing has become a standard tool for studying these interactions, but it has an important limitation. To sequence individual ...
Impact and correction of segmentation errors in spatial transcriptomics
Spatial transcriptomics is a powerful approach for studying how cells behave within intact tissues. By measuring where RNA molecules are located inside a tissue, scientists can connect gene activity to specific cell types and their surrounding environment. Imaging-based spatial ...
DBiTplus – integration of imaging-based and sequencing-based spatial omics mapping on the same tissue section
Researchers at Yale University have developed a new approach called DBiTplus, short for Deterministic Barcoding in Tissue sequencing plus, that overcomes this limitation. DBiTplus allows scientists to measure RNA and proteins from the same tissue section, creating a detailed ...
Spatial Touchstone brings quality control to spatial transcriptomics
A collaborative project led by St. Jude Children’s Research Hospital has created a comprehensive guide to help standardize spatial transcriptomics practices. Spatial transcriptomics provides a unique perspective on the genes that cells express and where those cells are located...
Nicheformer – a new foundation model that reveals how cells are organized in tissues
Missing Context in Single-Cell Data Single-cell RNA sequencing has transformed biology by showing which genes are active in individual cells. However, this approach requires cells to be removed from their natural environment, erasing information about their position and neighbors. ...
Slide-tags enables single-nucleus barcoding for multimodal spatial genomics
Understanding how cells are arranged in tissues is just as important as knowing what genes they are expressing. Traditional single-cell and single-nucleus RNA sequencing has given researchers valuable insights into gene activity, but until now, it has not been ...
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- BAP-seq – bioorthogonal masked acylating agents for proximity-dependent RNA labelling
- Single-cell RNA-seq of the rare virosphere reveals the native hosts of giant viruses in the marine environment
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